The Benefits and Challenges of adopting Java Microservices Architecture

Java microservice architecture is a groundbreaking approach to software development that is revolutionizing the industry. In addition, as per recent survey, nearly 70% of businesses are now using or planning to use microservice architecture in their development processes. Additionally, this method also divides large monolithic programs into smaller, independent services, each serving a distinct purpose. And when it comes to implementing microservices, Java is a popular choice for many developers.

Furthermore, one of the biggest advantages of Java Microservices Architecture is its ability to improve scalability and flexibility. In fact, a recent study found that companies using microservices architecture were able to increase their release frequency by up to 60%. This not only allows for a faster and more efficient development cycle, but also provides businesses with a competitive edge in their respective industries. 

However, it’s not just about the benefits of Java Microservices but also about the challenges you may face. From managing complex interactions between services to ensuring data consistency and reliability, there are many factors to consider when implementing microservices-based systems. 

And to know everything about Java Microservices architecture you must read this blog. 


Java Microservices is an architectural approach to building software applications that involves breaking large, monolithic applications into smaller, independent services. Developers use these services to perform specific functions and communicate with each other over a network using lightweight protocols such as HTTP or message queues. 

The design of Java Microservices facilitates the development, testing, deployment, and scaling of individual components of the application by making them highly modular and loosely coupled. In addition, developers develop and deploy each microservice independently, enabling faster release cycles and making it easier to maintain the applications over time. 

Additionally, Java is a popular language for developing microservices due to its object-oriented programming model, rich set of libraries, and strong support for concurrency and parallelism. Java microservices can be developed using a framework such as Spring Boot, which provides a lightweight and opinionated approach to building microservices. 

In a nutshell, Java microservices offer a flexible and scalable architecture that can help developers to develop and maintain complex applications with greater agility and efficiency. 


The architecture of Java Microservice is a combination of different architectural patterns, which you may see below;

  • Microservices Architecture

The main principle of microservice architecture is to create a set of independent, small, and self-contained services that work together to deliver the application’s functionality. Each service is in charge of a particular business capability, and services often communicate with one another via lightweight protocols like HTTP or SMS. Services in a microservice architecture must dynamically discover one another.

  • Service Registry and Discovery

In a microservice  architecture, services need to discover each other dynamically. A service registry is a centralized database that keeps track of all the services that are available in the system, along with their network locations. The discovery process involves querying the registry for available services. 

  • API Gateway 

An API gateway is a server that needs to discover each other dynamically. It serves as a single entry point for clients. It also provides a unified interface to access multiple microservices. The API gateway handles the routing and composition of requests, as well as security, rate limiting, and other cross-cutting concerns. 

  • Circuit Breaker

A design pattern known as a circuit breaker prevents a network or service failure from spreading to other services.  It acts as a safety net, detecting failures and temporarily blocking requests to  the affected service. This enables the system to function normally while the problem is being fixed

  • Event-Driven Architecture

Services communicate with one another in an event-driven architecture by publishing and subscribing to events. This allows for asynchronous communication, and services can be loosely coupled, which increases the system’s scalability and resilience. 

  • Containerization 

It is simpler to deploy and manage microservices by containerizing an application and its dependencies into a lightweight, portable container that offers a consistent runtime environment.

  • orchestration

Automation of container deployment, scaling, and management is accomplished through orchestration. Kubernetes is a popular orchestration tool that provides features such as discovery, load balancing, and automatic scaling. 


  1. Scalability 

Microservices enhance scalability by designing small, self-contained services that can scale up or down as needed. . By avoiding the need to scale the entire program, this makes it simpler to manage changes in demand.

  1. Flexibility

Offers flexibility to develop, deploy, and scale microservices independently, allowing teams to work in parallel and bring new features to market quickly.

  1. Resilience

Because microservices are self-contained, failures in one service don’t necessarily bring down the entire system. This makes it easier to isolate problems and recover more quickly from failures.

  1. Modularity 

Improves modularity by organizing microservices around business capabilities, making it easier to modify specific parts of the system without affecting other parts.

  1. Agility 

Microservices make it simpler to adapt to changes in the market or customer needs by enabling quicker development and deployment cycles.

  1. Technology diversity

Microservices architecture enables the use of a variety of programming languages and frameworks, allowing teams to choose the best tools for each individual service.

  1. DevOps enablement

With microservices architecture, DevOps practices can be applied more effectively, making it easier to automate deployments, testing, and monitoring.


  1. Service boundaries

Defining the boundaries of services can be challenging, as it requires breaking down monolithic systems into smaller, autonomous services that can operate independently.

  1. Data consistency

Maintaining data consistency across multiple services can be complex, as each service has its own database, and changes made in one service may not be immediately reflected in other services.

  1. Communication and coordination

Effective communication and coordination between microservices is essential to ensure that each service functions seamlessly with others. This requires implementing effective messaging protocols and ensuring that each service can work with different data formats.

  1. Deployment complexity

Deploying and managing multiple microservices can be challenging, as each service must be deployed separately and managed independently. This can require significant expertise and resources.

  1. Testing complexity

Testing microservices can be complex, as each service must be tested in isolation and as part of the larger system. This requires developing effective testing strategies and tools.

  1. Security 

Because each service could have unique security needs and weaknesses, securing microservices can be difficult. This requires implementing robust security protocols and ensuring that each service is properly secured.


  • Spring Boot
  • Micronaut
  • Quarkus 
  • Vert.x


As you have read how Java microservice architecture consists of many benefits which is enough to adopt it. Java Development Services can benefit greatly from Java Microservices Architecture. Although it has challenges, you may get rid of them by following proper planning. Additionally, As the famous software engineer Martin Fowler once said, “Microservices, or more precisely the microservice architecture, is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms.” Therefore, using this strategy, businesses may divide their large, complex apps into smaller, easier-to-manage parts that can be created and deployed separately.

Author Bio: Nitin Patil is a seasoned Sr. SEO Executive at Bigscal, a leading software development company. With over 7+ years of experience in the digital marketing industry, Nitin specializes in driving organic growth for businesses through search engine optimization strategies.

Community Tips

8 Java Programming Tricks Every Java Developer Should Know

Java is one of the most popular programming languages in the programming world, used by millions of developers to build complex software systems and applications. As a Java developer, it’s essential to stay up-to-date with the latest trends and techniques to remain competitive and produce high-quality code. In this article, we’ll explore eight Java programming tricks every Java developer should know, including how java developers for hire can help you implement them in your projects.

  • Use Lambda Expressions

Lambda expressions are a powerful feature introduced in Java 8 that allow you to write functional-style code with less boilerplate. With lambda expressions, you can define a method as a parameter to another method, reducing the amount of code you need to write. For example, instead of writing:

List<String> names = new ArrayList<>();
for (Person person : people) {

You can use a lambda expression like this:

List<String> names =

This code is more concise and easier to read, making your code more maintainable.

  • Use Optional Instead of Nulls

Nulls can cause many problems in Java code, including NullPointerExceptions, which can be difficult to debug. Instead of using nulls, use the Optional class, which allows you to represent an object that may or may not be present. Optional provides a safer and more elegant way to handle nulls in your code.

  • Use Streams for Collection Operations
    Streams provide a concise and powerful way to perform operations on collections in Java. With streams, you can perform operations like filtering, mapping, and reducing without the need for complex loops or temporary collections. Streams can significantly simplify your code and make it easier to read and maintain.
  • Use String.format for String Concatenation
    String concatenation can be a performance bottleneck in Java code, especially when concatenating large strings. Instead of using the + operator, use the String.format method to concatenate strings. String.format creates a formatted string that you can customize with placeholders and arguments, making your code more readable and efficient. 
public class StrFormat  
    /* Driver Code */  
    public static void main(String args[])  
        String s1 = new String("Hello");    //String 1  
        String s2 = new String(" World");    //String 2  
        String s = String.format("%s%s",s1,s2);   //String 3 to store the result  
            System.out.println(s.toString());  //Displays result  
  • Use Immutable Objects

Immutable objects are objects whose state cannot be changed after creation. Immutable objects are thread-safe and can simplify your code by eliminating the need for locks or synchronization. Use immutable objects whenever possible to improve the performance and reliability of your code.

String name = "baeldung";
String newName = name.replace("dung", "----");
assertEquals("baeldung", name);
assertEquals("bael----", newName);
  • Use Interface Default Methods

Default methods were introduced in Java 8 and allow you to add methods to an interface without breaking existing implementations. Default methods provide a powerful way to extend existing interfaces and create more flexible and maintainable code.

import java.time.*; 
public interface TimeClient {
    void setTime(int hour, int minute, int second);
    void setDate(int day, int month, int year);
    void setDateAndTime(int day, int month, int year,
                               int hour, int minute, int second);
    LocalDateTime getLocalDateTime();
  • Use Reflection Sparingly

Reflection is a powerful but dangerous feature in Java that allows you to inspect and modify the behaviour of a program at runtime. Reflection can be slow and error-prone, and should only be used when necessary. If possible, use other features of Java, such as interfaces, to achieve your goals.

import java.lang.reflect.*;

   public class DumpMethods {
      public static void main(String args[])
         try {
            Class c = Class.forName(args[0]);
            Method m[] = c.getDeclaredMethods();
            for (int i = 0; i < m.length; i++)
         catch (Throwable e) {
  • Use Enumerations Instead of Constants

Enumerations are a more powerful and flexible way to represent constants in Java. Enumerations allow you to group related constants and define their behaviour, making your code more expressive and maintainable. Use enumerations whenever possible to avoid the problems associated with traditional constants.

public class Main {
  enum Level {

  public static void main(String[] args) {
    Level myVar = Level.MEDIUM; 
  • Use Try-With-Resources for Resource Management
    Try-With-Resources is a feature introduced in Java 7 that allows you to automatically close resources such as files, sockets, and database connections after they are no longer needed. Try-With-Resources can simplify your code and ensure that resources are always properly closed, reducing the risk of resource leaks and other problems.
  • Use Javadoc to Document Your Code
    Javadoc is a powerful tool for documenting your Java code. With Javadoc, you can create professional-looking documentation for your code that can be easily shared with other developers. Javadoc can also help you understand your own code better and identify potential problems and bugs.
  • Use Dependency Injection for Loose Coupling
    Dependency Injection is a design pattern that promotes loose coupling between components of a system. With Dependency Injection, you can inject dependencies into a class instead of creating them inside the class, reducing the complexity and dependencies of your code. Dependency Injection can also make your code more flexible and easier to test, making it a valuable technique for Java developers to learn.

Use Unit Testing for Quality Assurance

Unit Testing is a crucial technique for ensuring the quality and correctness of your Java code. With Unit Testing, you can test individual units of code in isolation, identifying and fixing problems before they become larger issues. Unit Testing can also improve the maintainability of your code by ensuring that changes and updates don’t introduce unexpected side effects or bugs. As a Java developer, it’s essential to understand and practise Unit Testing to produce high-quality, reliable code.


Java developers for hire can help you implement these programming tricks in your projects. The tricks we mentioned can improve the quality and efficiency of your code, and help you stay up-to-date with the latest trends and techniques in Java programming. But if you need to do it asap, Java developers for hire can help you implement these programming tricks in your projects.


Best way to hire a Senior Java Programmer

Without a reliable and trustworthy web application to depend on in today’s competitive business environment, it might be difficult to prosper and survive.

A website not only provides a multitude of features and services, but it also makes it extremely easy for business organisations to organise their work and improve their internal communication via the use of several web-based apps. Java has been actively employed by developers to give high-end software and online apps to customers regardless of whether they are working on the internet or an organisation’s private intranet.

In the following section, we are going to talk about the multitude of benefits that this platform offers, as well as the reasons why you should hire Java developers. Read on for more information.

Java is now one of the programming languages that are in most demand worldwide. Because of the important function, it plays in the operations of your main company, you will need to find the most qualified individuals to join your team. Everything you need to know to successfully attract Java developers is included in this guide.

Although Java is a general-purpose programming language that uses statically typed expressions, it is also an object-oriented and concurrent language. Java was intended to be a WORA language, which stands for “write once, run anywhere.” This means that the language should be able to operate on any platform and with as few dependencies as possible with the support of the Java Virtual Machine (JVM). There is no such thing as speed in languages; all that is required is linguistics. If you want to assess how quickly anything is implemented, you need to choose distinct implementations to compare with one another. Backend web development often makes use of languages written in Java. Backend web development refers to the portion of web development that is concerned with the creation of the software system that may be executed on the server. According to a poll that was conducted among developers on Stack Overflow, java is the most prevalent kind of development.

Java is an older programming language, yet it is still widely used

In the early 2000s, commercial applications were among the first to start making widespread use of Java. It was designed with a few primary goals in mind, including ease of use, durability, and mobility. It is clear how these fundamental characteristics contributed to Java’s rise to prominence as a language of choice, one that is today used in every industry and application layer possible. All of these things may be developed in Java by making use of sophisticated frameworks and tools, including database access, system behavior, service publishing and access, and individual development (mobile, web, and desktop). In addition, Java can be found on every platform imaginable, from SIM cards in mobile smartphones to the high-end servers that operate the cloud. It can even be found on implanted and Internet of Things (IoT) devices. A software developer can’t make a mistake by deciding to study Java. Approximately 51 billion Java virtual machines are operating, which means that well-paying employment is assured for Java applications for many years to come. 98 percent of the Fortune 100 companies are actively employing Java workers.

Java is still one of the most widely used programming languages, and as a result, programmers who are proficient in Java are in high demand. The programming language is used by a variety of significant organizations to build and maintain their internationally recognized products. Java is well-known for the rapid processing speed it offers in software, computer games, and apps for desktop computers as well as mobile devices. It is used in the process of developing software as well as web-based applications for a variety of platforms. It has gained a lot of popularity because it is simple to use for newcomers, even though it may still take some time to grasp.

The creation of programs and software via the use of the programming language Java falls within the purview of a Java developer. A Java developer is a specific sort of programmer that may work in conjunction with web developers and software engineers to incorporate Java into commercial applications, software, and websites. C#, the primary rival to Java, is seeing a decline in market share, in contrast to Python’s competitors R and Ruby, which are more or less remaining stable. This post demonstrates the procedures that need to be taken to hire an acceptable Java developer, which is a challenging process in and of itself. Let’s begin by discussing how to choose a qualified candidate out of a heap of resumes submitted by Java engineers.

A Brief Observation Regarding the salary of Java Developers

You may be wondering what elements have an impact on the salary of a Java developer. There are two primary contributions, which are as follows:

  1. Experience. Even within the seniority level of a Junior Java developer role, more experienced applicants anticipate earning higher money. If you are in the process of recruiting for this position, keep this in mind.
  2. Skills. Developers that possess talents that are in higher demand will be compensated more. Candidates that have expertise in Java/J2EE are often compensated at a higher rate on average. In addition, since developers are such an important part of the process of producing your product, you should look for ones that share the values of your organization. In the long run, it is to the advantage of both parties since developers who are enthusiastic about their work often better represent the company’s ideals in the end product that the customers view.

When looking to hire a Java programmer, what are the best practices to follow?

  1. It may feel like a never-ending hunt for a decent employee while you are in the process of looking for one. There is a significant amount of demand for highly qualified workers all around the globe, and this is especially true when recruiting Java developers is taken into consideration.
  2. Java is the programming language of choice for corporations since it is the most reliable, versatile, and safe option available. As a result of this, Java developers will be among the professions with the second greatest demand in the year 2022.
  3. When looking to recruit Java developers, you must find individuals who are not just technically competent but also excellent communicators and who are aware of what they are doing.
  4. But where can you get people with such qualifications? There are not nearly enough people looking for jobs who have these specialized skill sets, even though there is a significant need for them.
  5. When you confine your search to a certain location, whether it be a city or even a nation, you will quickly discover that the pool of potential individuals is far less than you would have anticipated. 

The following recommendations for searching for an appropriate Java developer:

  1. Employing a Java software developer: The first question that has to be addressed is, “from where can I hire java programmer?” The first place that employers search for people with Java development experience is on several job portals. However, there are online communities and specialized forums such as GitHub, Stack Overflow, and others that can give you a reasonable idea about the level of expertise of the participating developers. This is because people typically use these platforms to demonstrate their level of technical expertise. In addition to this, Java hackathons and conferences provide the opportunity for recruiters to physically connect with developers while also expanding their network of contacts.
  2. A good old-fashioned JD will do the trick: The job description must make it very apparent which particular abilities a potential Java programmer should possess to be considered for the position. Your efforts to filter applicants would be reduced as a result since individuals who exhibit these attributes are more likely to apply for the job. The JD ought to, in an ideal world, contain the requisite years of experience, the required skill set, the domain of the project, KRAs, and so forth.
  3. Examine Your Java Certifications There are many different kinds of Java certifications, and typically, Java developers will earn them to confirm their expertise and demonstrate that they are technically valuable. The recruiter saves a lot of time by having an in-depth grasp of these qualifications, which helps eliminate unsuitable applicants during the basic screening process itself.

What qualities must a Java developer have when you hire?

  1. Skill evaluations

It is necessary to do skill evaluations correctly: In an ideal world, the potential Java developers would have some familiarity with the languages, frameworks, and tools that are used by the JVM when it comes to developing, testing, and designing Java applications. A solid foundation of advanced-level object-oriented features and ideas is also required, in addition to the aforementioned need. Arranging for a developer to have a technical interview with either the team lead or the project manager is one way to evaluate the developer’s talents and level of technical expertise. In addition to this, his coding and debugging abilities need to be evaluated through the use of a practice round. This helps us determine the quality of the candidate’s code, which is another aspect of the evaluation.

  1. A superb cultural fit

No matter where you are in the recruiting process, a red flag should be raised if a Java programmer has the requisite Java competence but lacks the mindset to fit with the culture of your organization. This is the case even if they have the necessary Java expertise. During the interview process, Java programmers have the opportunity to exhibit their skills; but, before you offer them a contract, you should require that they meet with other members of your team. If you don’t sense a connection with that individual, it’s possible that they aren’t the right fit for you. When looking to hire a Java developer, finding someone who is a good cultural fit for your team should be one of your top priorities. You may need to broaden your search to find someone who can contribute to your team right away, so be prepared to do so. However, bear in mind that locating a Java programmer who is compatible with the culture of your business is not only essential when making new hires, but is also something to consider in the market for contract work. 

You may be able to find Java programmers who will remain with you for long-term projects and maybe even become permanent fixtures if you take the additional time necessary to verify that they are a cultural match inside your company.

  1. Problem-solving skills

Every Java programmer needs to have the ability to produce, deploy, and effectively manage code. In addition to these primary roles, they should also be responsible for fixing any problems that come up throughout the testing cycle and delivering implementable solutions. When making hires, you won’t only be able to glance at a candidate’s CV to identify whether they have the characteristics you want in a Java programmer; you’ll need to go deeper. To find out, you should put them through a technical exam in which they have to show their ability to solve problems. However, regardless of how capable a Java programmer is, if they fail to include any advanced techniques in their CV, you should be sure to investigate further to see whether they fit your requirements.

  1. A flexible technique for Java programming

Even if a certain set of skills may be necessary, it could be more beneficial in the long term to take a broader perspective and focus on recruiting for the future. If you do not do a thorough study of a candidate’s curriculum vitae while searching for the right Java programmer, you may find out that they have only worked with a single version of Java, which is probably not a suitable match for your company if you want to grow it. Even if a Java programmer has only ever worked with a single platform in their previous job, a developer who is passionate about their profession will make the effort to learn new skills that will help them in the long run. This is because new skills will help them stay competitive in their field.

Examine the perpetual and signed agreement marketplaces for a Java programmer who can exemplify technical ability while also being encouraged to gain new methods and widen on theories of Java knowledge. This will help you avoid hiring a one-trick developer and ensure that you are not hiring someone with limited Java knowledge.

Why Java Outsourcing?

Even while Java is the technology of the moment for major corporations and firms that often choose to engage a specialized Java developer to instantly solve any challenges related to Java, there are a variety of benefits to engaging an external agency for the development of your software. Work in Java development is often outsourced by businesses to make cost and time savings, and frequently to make up for a lack of in-house technical skills. As a result of the vast skill pool of software engineers available in a variety of locations, outsourcing Java projects have become more popular. 

Outsourcing has several benefits, some of which are listed here 

  1. If one chooses to outsource the Java development assignment, then the entire cost of the project will be reduced by a significant amount.
  2. There is no need for one to spend money on technology, elaborate systems, or infrastructure.
  3. While the team you outsourced to works on the project, you will have a lot more free time on your hands, which will allow you to concentrate on other important responsibilities.
  4. The selection of the team is a challenging undertaking, and the cost of the project will increase with each incorrect pick. Because you outsourced this task, you no longer have to worry about it.
  5. Talking to the customer support team at any time is the best way to have one’s questions answered.
  6. You are no longer responsible for HR or administrative matters. You just need to keep an eye on how the project is moving along as a whole.
  7. You do not have to make concessions because of the technological inefficiencies involved since you have the legal right to request a certain feature for the project.

Infographic: Programming languages adoption trends 2020

Languages are a beloved subject of debate and the kernels of some of the strongest developer communities. The choice of programming language matters deeply to developers because they want to keep their skills up to date and marketable. They matter to toolmakers too, because they want to make sure they provide the most useful SDKs. So which programming languages had notable changes in adoption trends in the last 3 years? Find the answers in our infographic with key findings from our Developer Economics 19th edition survey, which ran in June-August 2020 and reached 17,000 developers in 159 countries. 

JavaScript is the most popular programming language

As of Q3 2020, 12.4M developers globally were using JavaScript. We also estimate that in mid-2020 there were 21.3M active software developers in the world. So, 58% of all developers use JavaScript. Notably, the JavaScript community has been growing in size consistently for the past three years. Between Q2 2017 and Q3 2020, nearly 5M developers joined the community – by far the highest growth in absolute terms across all languages. Even in software sectors where JavaScript is least popular, like data science or AR/VR, over a fifth of developers use it in their projects. 

It’s a good idea to learn Python

For the second half-year period in a row, Python is the most widely adopted language behind JavaScript. Python now counts 9M users, after adding 2.2M net new developers in the past year alone, outranking Java at the beginning of 2020. The rise of data science and machine learning (ML) is a clear factor in its popularity. An impressive 77% of ML developers and data scientists currently use Python. For perspective, only 22% use R, the other language often associated with data science.

What’s new with Java and other well- established programming languages?

Java, with over 8M active users worldwide, is the cornerstone of the mobile app ecosystem – Android – as well as one of the most important general-purpose languages. It’s adoption may have remained stable in the past six months but, in the overall picture, the Java community has gained 1.6M developers since mid-2017, which corresponds to a 24% growth.

The group of major, well-established languages is completed with C/C++ (6.3M), PHP (6.1M) and C# (6M). The fact that C# lost three places in the ranking of language communities during the last three years is mostly explained by its slower growth compared to C/C++ and PHP. C and C++ remain core languages in IoT projects (for both on-device and application-level coding), whereas PHP is still the second most commonly used language in web applications, after JavaScript. On the other hand, C# may be sustaining its dominance in the game and AR/VR developer ecosystems, but it seems to be losing its edge in desktop development – possibly due to the emergence of cross-platform tools based on web technologies.

Android developers behind Kotlin growth

Kotlin is one of the fastest growing language communities, having increased more than two-fold in size since the end of 2017, from 1.1M in Q4 2017 to 2.3M in Q3 2020. This is also very evident from Kotlin’s ranking, where it moved from 11th to ninth place during that period – a trend that’s largely attributed to Google’s decision to make Kotlin its preferred language for Android development. 

Swift surpassed Kotlin in popularity this year, after attracting slightly more net new developers in the first half of 2020 (400k vs 300k). Since Swift became the default language for development across all Apple platforms, the adoption of Objective C has been decreasing steadily. This phase-out from the Apple app ecosystem is also matched by a significant drop in the rank of Objective C, from ninth to 12th place. 

Finally, the more niche languages – Go, Ruby, Rust, and Lua – are still much smaller, with up to 1.5M active software developers each. Ruby and Lua have been around for more than two decades now, but their communities have essentially stopped growing in the last three years. On the contrary, Go and Rust appear to be actively adding developers, although it is still unclear whether the two languages will climb the programming language ranking in the coming period.

What’s your favourite programming language? Take our Developer Economics 20th edition survey to support your choice!

Infographic: Programming languages adoption trends 2020

The Queen of Programming Languages with 11M+ Users

The choice of programming language matters deeply to developers because they want to keep their skills up to date and marketable. Programming Languages are a beloved subject of debate and the kernels of some of the strongest developer communities. They matter to toolmakers too, as they want to make sure they provide the most useful SDKs.

Here is an update on Programming Language Communities, from our State of the Developer Nation Report 17th Edition.

It can be hard to assess how widely used a programming language is. The indices available from players like Tiobe, Redmonk, Stack Overflow’s yearly survey, or Github’s Octoverse are great, but mostly offer only relative comparisons between languages, providing no sense of the absolute size of each community. They may also be biased geographically, or skewed towards certain fields of software development, or open source developers.

The estimates we present here look at active software developers using each programming language, across the globe and across all kinds of programmers.

They are based on two pieces of data:

First, our independent estimate of the global number of software developers, which we published for the first time in 2017. We estimate that in mid 2019 there are 18 million active software developers in the world.

Second, our large-scale, low-bias surveys which reach tens of thousands of developers every six months. In the surveys, we consistently ask developers about their use of programming languages across ten areas of development, giving us rich and reliable information about who uses each language and in which context.


11M+ developers use Javascript

The most popular programming language by a wide margin is Javascript, including derivatives like TypeScript and CoffeeScript. The Javascript community counts over 11 million active developers. Even in software sectors where Javascript is least popular like machine learning or on-device code in IoT, over a fifth of developers use it for their projects. 

Programming language communities Q2 2019
Programming language communities Q2 2019

The rise of machine learning is a clear factor in the success of Python:

8 in 10 machine learning developers use Python in their work (compared to just 25% using R, the other language often associated with data science). Java, of course, is a cornerstone of the mobile app ecosystem (Android) as well as a great general-purpose language.

Language use is not static: developers drop and adopt new languages all the time

It would appear that it is not meaningful to speak of “Java developers” or “Python developers” in any fundamental sense, other than that they use those languages at a certain point in time. While we see a net decline in the use of most languages by our repeat respondents, some languages reverse that trend and show significant growth. The first of these is Kotlin, which we are confident to say is the rising star in the programming language firmament.

Kotlin’s rank among programming languages moved from 11th to 8th place in just a year, and one in ten developers now use the language.

Rank of programming language communities 2017-2019
Rank of programming language communities 2017-2019

Tracking the ever-changing landscape of the software development ecosystem is why we run our Developer Economics surveys twice a year and there is one live right now. To track changes on programming languages, tools and platforms we need you to share with us your coding experiences!  We would be very interested to know what programming languages, hardware, frameworks and platforms you use, and the types of projects you’re working on.

Has the new Oculus Quest piqued your interest and restarted the heart of VR development? Or is AR and mixed reality where it really is? Help us tell the technology leaders what you think, and by doing so become part of the change you want to see in the tools you use.


What is the best programming language for Machine Learning?

Q&A sites and data science forums are buzzing with the same questions over and over again: I’m new in data science, what language should I learn? What’s the best machine learning language?


There’s an abundance of articles attempting to answer these questions, either based on personal experience or on job offer data. Τhere’s so much more activity in machine learning than job offers in the West can describe, however, and peer opinions are of course very valuable but often conflicting and as such may confuse the novices. We turned instead to our hard data from 2,000+ data scientists and machine learning developers who responded to our latest survey about which languages they use and what projects they’re working on – along with many other interesting things about their machine learning activities and training. Then, being data scientists ourselves, we couldn’t help but run a few models to see which are the most important factors that are correlated to language selection. We compared the top-5 languages and the results prove that there is no simple answer to the “which language?” question. It depends on what you’re trying to build, what your background is and why you got involved in machine learning in the first place.

Which machine learning language is the most popular overall?

First, let’s look at the overall popularity of machine learning languages. Python leads the pack, with 57% of data scientists and machine learning developers using it and 33% prioritising it for development. Little wonder, given all the evolution in the deep learning Python frameworks over the past 2 years, including the release of TensorFlow and a wide selection of other libraries. Python is often compared to R, but they are nowhere near comparable in terms of popularity: R comes fourth in overall usage (31%) and fifth in prioritisation (5%). R is in fact the language with the lowest prioritisation-to-usage ratio among the five, with only 17% of developers who use it prioritising it. This means that in most cases R is a complementary language, not a first choice. The same ratio for Python is at 58%, the highest by far among the five languages, a clear indication that the usage trends of Python are the exact opposite to those of R. Not only is Python the most widely used language, it is also the primary choice for the majority of its users. C/C++ is a distant second to Python, both in usage (44%) and prioritisation (19%). Java follows C/C++ very closely, while JavaScript comes fifth in usage, although with a slightly better prioritisation performance than R (7%). We asked our respondents about other languages used in machine learning, including the usual suspects of Julia, Scala, Ruby, Octave, MATLAB and SAS, but they all fall below the 5% mark of prioritisation and below 26% of usage. We therefore focused our attention on the top-5 languages.

Python is prioritised in applications where Java is not.

Our data reveals that the most decisive factor when selecting a language for machine learning is the type of project you’ll be working on – your application area. In our survey we asked developers about 17 different application areas while also providing our respondents with the opportunity to tell us that they’re still exploring options, not actively working on any area. Here we present the top and bottom three areas per language: the ones where developers prioritise each language the most and the least.

Machine learning scientists working on sentiment analysis prioritise Python (44%) and R (11%) more and JavaScript (2%) and Java (15%) less than developers working on other areas. In contrast, Java is prioritised more by those working on network security / cyber attacks and fraud detection, the two areas where Python is the least prioritised. Network security and fraud detection algorithms are built or consumed mostly in large organisations – and especially in financial institutions – where Java is a favourite of most internal development teams. In areas that are less enterprise-focused, such as natural language processing (NLP) and sentiment analysis, developers opt for Python which offers an easier and faster way to build highly performing algorithms, due to the extensive collection of specialised libraries that come with it.

Artificial Intelligence (AI) in games (29%) and robot locomotion (27%) are the two areas where C/C++ is favoured the most, given the level of control, high performance and efficiency required. Here a lower level programming language such as C/C++ that comes with highly sophisticated AI libraries is a natural choice, while R, designed for statistical analysis and visualisations, is deemed mostly irrelevant. AI in games (3%) and robot locomotion(1%)  are the two areas where R is prioritised the least, followed by speech recognition where the case is similar.

Other than in sentiment analysis, R is also relatively highly prioritised – as compared to other application areas – in bioengineering and bioinformatics (11%), an area where both Java and JavaScript are not favoured. Given the long-standing use of R in biomedical statistics, both inside and outside academia, it’s no surprise that it’s one of the areas where it’s used the most. Finally, our data shows that developers new to data science and machine learning who are still exploring options prioritise JavaScript more than others (11%) and Java less than others (13%). These are in many cases developers who are experimenting with machine learning through the use of a 3rd-party machine learning API in a web application.


Professional background is pivotal in selecting a machine learning language.

Second to the application area, the professional background is also pivotal in selecting a machine learning language: the developers prioritising  the top-five languages more than others come from five different backgrounds. Python is prioritised the most by those for whom data science is the first profession or field of study (38%). This indicates that Python has by now become an integral part of data science – it has evolved into the native language of data scientists. The same can not be said for R, which is mostly prioritised by data analysts and statisticians (14%), as the language was initially created for them, replacing S.

Front-end web developers extend their use of JavaScript to machine learning, 16% prioritising it for that purpose, while staying clear of the cumbersome C/C++ (8%). At the exact opposite stand embedded computing hardware / electronics engineers who go for C/C++ more than others, while avoiding JavaScript, Java and R more than others. Given their investment in mastering C/C++ in their engineering life, it would make no sense to settle for a language that would compromise their level of control over their application. Embedded computing hardware engineers are also the most likely to be working on near-the-hardware machine learning projects, such as IoT edge analytics projects, where hardware may force their language selection. Our data confirms that their involvement is significantly above average in industrial maintenance, image classification and robot locomotion projects among others.

For Java, it’s the front-end desktop application developers who prioritise it more than others (21%), which is also inline with its use mostly in enterprise-focused applications as noted earlier. Enterprise developers tend to use Java in all projects, including machine learning. The company directive in this case is also evident from the third factor that is strongly correlated to language prioritisation – the reason to get into machine learning. Java is prioritised the most (27%) by developers who got into machine learning because their boss or company asked them to. It is the least preferred (14%) by those who got into the field just because they were curious to see what all the fuss was about – Java is not a language that you normally learn just for fun! It is Python that the curious prioritise more than others (38%), another indication that Python is recognised as the main language that one needs to experiment with to find out what machine learning is all about.

It seems that some universities teaching data science courses still need to catch up with this notion though. Developers who say that they got into machine learning because data science is/was part of their university degree are the least likely to prioritise Python (26%) and the most likely to prioritise R (7%) as compared to others. There is evidently still a favourable bias towards R within statistics circles in academia – where it was born – but as data science and machine learning gravitate more towards computing, the trend is fading away. Those with university training in data science may favour it more than others, but in absolute terms it’s still only a small fraction of that group too that will go for R first.

C/C++ is prioritised more by those who want to enhance their existing apps/projects with machine learning (20%) and less by those who hope to build new highly competitive apps based on machine learning (14%). This pattern points again to C/C++ being mostly used in engineering projects and IoT or AR/VR apps, most likely already written in C/C++, to which ML-supported functionality is being added. When building a new app from scratch – especially one using NLP for chatbots – there’s no particular reason to use C/C++, while there are plenty of reasons to opt for languages that offer highly-specialised libraries, such as Python. These languages can more quickly and easily yield highly-performing algorithms that may offer a competitive advantage in new ML-centric apps.

Finally, contractors who got into machine learning to increase their chances of securing highly-profitable projects prioritise JavaScript more than others (8%). These are probably JavaScript developers building web applications to which they are adding a machine learning API. An example would be visualising the results of a machine learning algorithm on a web-based dashboard.

There is no such thing as a ‘best language for machine learning’.

Our data shows that popularity is not a good yardstick to use when selecting a programming language for machine learning and data science. There is no such thing as a ‘best language for machine learning’ and it all depends on what you want to build, where you’re coming from and why you got involved in machine learning. In most cases developers port the language they were already using into machine learning, especially if they are to use it in projects adjacent to their previous work – such as engineering projects for C/C++ developers or web visualisations for JavaScript developers.

If your first ever contact with programming is through machine learning, then your peers in our survey point to Python as the best option, given its wealth of libraries and ease of use. If, on the other hand, you’re dreaming of a job in an enterprise environment, be prepared to use Java. Whatever the case, these are exciting times for machine learning and the journey is guaranteed to be a mind-blowing one, irrespective of the language you opt for. Enjoy the ride!